Motion Primitives-based Navigation Planning using Deep Collision Prediction
Huan Nguyen,Sondre Holm Fyhn,Paolo De Petris,Kostas Alexis,Huan Nguyen,Sondre Holm Fyhn,Paolo De Petris,Kostas Alexis
This paper contributes a method to design a novel navigation planner exploiting a learning-based collision prediction network. The neural network is tasked to predict the collision cost of each action sequence in a predefined motion primitives library in the robot's velocity-steering angle space, given only the current depth image and the estimated linear and angular velocities of the robot. Furth...
